The Fine Print: The following comments are owned by whoever posted them. We are not responsible for them in any way.
Without JavaScript enabled, you might want to
use the classic discussion system instead. If you login, you can remember this preference.

I think the big blocker for using artificial intelligence techniques is that many people have tried to use them and been burned when the technique they applied performs marginally better than the naive algorithm. I've studied, at least briefly, heuristic searches, simulated annealing, min-max trees, bayesian networks, hidden markov models, etc. If I had to implement one I could do it, but the bigger problem is choosing the right tool for the job and releasing maintainable code. Real life problems just don't

The other tricky problem when using AI-type systems is your evaluation can in some cases fall victim to observation biases.In order to test the AI system, you use it on a problem domain you already understand. So when you as an expert observer look at the results, they can appear underwhelming, since you can see how you would write a simple naive algorithm to achieve similar results.

And if you use it on a problem domain you DON'T understand, you aren't in a position to evaluate the results.